Abstract
Nowadays, with the massive integration of distributed renewable generation, electric vehicles... to the distribution level of the electricity grid, the traditional strategy for monitoring distribution systems is no more valid. In fact, Distribution Networks should become observable and controlled in real time in the same way as the transmission systems. Therefore, Distribution System State Estimation (DSSE) represents a relevant research topic to embrace the new conjuncture of Smart Grid, new techniques should be developed to ensure the observability and manage the bidirectional power flows generated by renewable resources. This paper provides a detailed survey of DSSE techniques available in literature: DSSE techniques based on adapting Weighted Least Squares Algorithm from transmission to distribution network according to the different state variables developed (Node voltage, Branch current, Branch power...) and DSSE methods based on Evolutionary Algorithms (Artificial Neural Network, Fuzzy Logic, Particle Swarm Optimization...) are presented. The advantages and disadvantages of each method are discussed finally, directions for future research arc suggested.